Mathematics is the foundation of many STEM fields and success in mathematics is a catalyst for success in other scientific disciplines. Increasing the participation of women and other under-represented groups in the mathematics profession builds human capital that produces a diverse pool of problem solvers in business and industry, research mathematicians, faculty at all levels, and role models for the next generation. Existing support and enrichment programs have targeted women in mathematics at different stages in their undergraduate and graduate education, with different strategies to building community, creating a sense of belonging, and promoting a growth mind set. These strategies challenge some of the most common obstacles to success, including isolation, stereotype threat, not committing to mathematics early enough, and imposter syndrome. Acknowledging the diversity among women in terms of socio-economic background and educational background, this project proposes to examine the effectiveness of these programs through the lens of two primary questions: (1) Which elements of these programs are most critical in the success of women, as a function of their position along these distinct diversity axes?, and (2) which features of these programs are most effective as a function of the stage of the participant's career? These questions are guided by the rationale that a better understanding of, and improved pathways by, which programs recruit and retain undergraduate and graduate women in mathematics has the strong potential to increase the representation of women among mathematics PhDs nationwide.
This project seeks to increase and diversify the number of professional mathematicians in the United States by identifying and proliferating best practices and known mechanisms for increasing the success of women in mathematics graduate programs, particularly women from under-represented groups. The PIs on this proposal, all of whom are leaders of initiatives that have been active for nearly two decades, will work with experts in management, data collection and reporting, and communications to address the following three challenges: (1) develop a common system of measuring the effectiveness of each element in these initiatives; (2) develop a process for effective, collective decision making; and (3) create connections between existing activities and resources. This project is both exploratory research and effectiveness research. The project team first will explore the contextual factors that serve to support or inhibit female pursuit of mathematics doctorates by interviewing a variety of women who were undergraduate mathematics majors in the past, as well as current professional mathematicians. They then will use this information to better understand the most effective features of various current and past initiatives that are trying to increase the participation of women in advanced mathematics. A key stakeholder meeting will develop a process for effective, collective decision-making, to utilize what the project team learns from the interviews. The leadership team will develop a website with discussion board and social media components to highlight best practices and facilitate a virtual community for women interested in mathematics. Finally, a distillation of program elements and their targeted effectiveness will inform the selection of interconnected activities to test on a scalable model. These prototypes will be implemented at several sites chosen to represent a diversity of constituencies and local support infrastructure.
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TEAM MEMBERS:
Judy WalkerAmi RadunskayaRuth HaasDeanna Haunsperger
This collaborative project aims to establish a national computational resource to move the research community much closer to the realization of the goal of the Tree of Life initiative, namely, to reconstruct the evolutionary history of all organisms. This goal is the computational Grand Challenge of evolutionary biology. Current methods are limited to problems several orders of magnitude smaller, and they fail to provide sufficient accuracy at the high end of their range. The planned resource will be designed as an incubator to promote the development of new ideas for this enormously challenging computational task; it will create a forum for experimentalists, computational biologists, and computer scientists to share data, compare methods, and analyze results, thereby speeding up tool development while also sustaining current biological research projects. The resource will be composed of a large computational platform, a collection of interoperable high-performance software for phylogenetic analysis, and a large database of datasets, both real and simulated, and their analyses; it will be accessible through any Web browser by developers, researchers, and educators. The software, freely available in source form, will be usable on scales varying from laptops to high-performance, Grid-enabled, compute engines such as this project's platform, and will be packaged to be compatible with current popular tools. In order to build this resource, this collaborative project will support research programs in phyloinformatics (databases to store multilevel data with detailed annotations and to support complex, tree-oriented queries), in optimization algorithms, Bayesian inference, and symbolic manipulation for phylogeny reconstruction, and in simulation of branching evolution at the genomic level, all within the context of a virtual collaborative center. Biology, and phylogeny in particular, have been almost completely redefined by modern information technology, both in terms of data acquisition and in terms of analysis. Phylogeneticists have formulated specific models and questions that can now be addressed using recent advances in database technology and optimization algorithms. The time is thus exactly right for a close collaboration of biologists and computer scientists to address the IT issues in phylogenetics, many of which call for novel approaches, due to a combination of combinatorial difficulty and overall scale. The project research team includes computer scientists working in databases, algorithm design, algorithm engineering, and high-performance computing, evolutionary biologists and systematists, bioinformaticians, and biostatisticians, with a history of successful collaboration and a record of fundamental contributions, to provide the required breadth and depth. This project will bring together researchers from many areas and foster new types of collaborations and new styles of research in computational biology; moreover, the interaction of algorithms, databases, modeling, and biology will give new impetus and new directions in each area. It will help create the computational infrastructure that the research community will use over the next decades, as more whole genomes are sequenced and enough data are collected to attempt the inference of the Tree of Life. The project will help evolutionary biologists understand the mechanisms of evolution, the relationships among evolution, structure, and function of biomolecules, and a host of other research problems in biology, eventually leading to major progress in ecology, pharmaceutics, forensics, and security. The project will publicize evolution, genomics, and bioinformatics through informal education programs at museum partners of the collaborating institutions. It also will motivate high-school students and college undergraduates to pursue careers in bioinformatics. The project provides an extraordinary opportunity to train students, both undergraduate and graduate, as well as postdoctoral researchers, in one of the most exciting interdisciplinary areas in science. The collaborating institutions serve a large number of underrepresented groups and are committed to increasing their participation in research.
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TEAM MEMBERS:
Tandy WarnowDavid HillisLauren MeyersDaniel MirankerWarren Hunt, Jr.
The Franklin Institute proposes to establish the Science Learning Network (SLN), a unique online collaborative of science museums, industry and schools to support the teaching and learning of science, mathematics and technology (SMT) in grades K-8. The SLN will integrate the educational resources offered by science/technology centers with the power of telecomputing networking to provide powerful new support for teacher development and science learning. By December 1997 the SLN will develop and evaluate the following: UniVERSE - an online SMT database and software package which will provide interactive capabilities to actively and intelligently assist K-8 classroom teachers in their Internet explorations, much like an electronic "librarian." Online Museum Collaborative - a national consortium of science museums (The Franklin Institute, the Exploratorium, Oregon Museum of Science and Industry, Museum of Science - Boston, and Science Museum of Minnesota) that will pool their resources and expertise to create online assets and provide ongoing professional development on telecomputing networking for precollege SMT teachers. Online Demonstration Schools - a network of K-8 schools, working in collaboration with consortium museums and Unisys Corporation volunteers as demonstration sites for online teaching and learning in SMT. Over the course of three years, the SLN will provide direct support to 180 teachers and 3,000 K-8 students in the online demonstration schools. Through existing teacher networks, each museum will offer professional development for an additional 200 teachers each year. The Urban Systemic Initiatives in Philadelphia and Miami offer the potential for broader, systemic impact in those cities. By the end of the grant period, the SLN will provide field- tested models of a new kind of online SMT community through the collaboration of science museums with industry and schools. The sustainable impact of the SLN will be assured by UniVERSE's status as a publicly accessible database and software package and the development of the national consortium of online museums, whose network resources will be made available on an ongoing basis to educators. The three-year formative development of the online demonstration schools will contribute vital data to precollegiate school reform in SMT, showing how schools build capacity to become members of the online community and demonstrating how teaching and learning are enhanced by online resources. Unisys Corporation has pledged its support to this project and will provide matching funds for up to 40% of the total NSF award.
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TEAM MEMBERS:
Stephen BaumannWayne RansomPaul Helfrich